On the reduction of complexity in the architecture of fuzzy ARTMAP with dynamic decay adjustment
This paper presents a hybrid network (FAMDDA-T) comprising the Fuzzy ARTMAP (FAM) neural network and the Dynamic Decay Adjustment (DDA) algorithm with an online pruning strategy. Twelve benchmark datasets are used to demonstrate the effectiveness of FAMDDA-T. The results of FAMDDA-T are compared wit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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ELSEVIER SCIENCE BV
2006
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| Subjects: | |
| Online Access: | http://shdl.mmu.edu.my/3247/ http://shdl.mmu.edu.my/3247/1/1302.pdf |
| Summary: | This paper presents a hybrid network (FAMDDA-T) comprising the Fuzzy ARTMAP (FAM) neural network and the Dynamic Decay Adjustment (DDA) algorithm with an online pruning strategy. Twelve benchmark datasets are used to demonstrate the effectiveness of FAMDDA-T. The results of FAMDDA-T are compared with those of FAMDDA (without pruning), and the Radial Basis Function Network with DDA (RBFN-DDA) as well as its pruning version (RBFN-DDA-T). It is observed that, when compared with other DDA-based networks, FAMDDA-T is able to form a parsimonious network structure and, at the same time, to maintain a high level of network generalization in tackling pattern classification problems. (c) 2006 Elsevier B.V. All rights reserved. |
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